Mathematical Model-Based Optimization of Continuous Flow Photobioreactor Operating at Steady State Using MATLAB Optimization Function

Abstract

AbstractMicroalgae have received great attention recently due to its potential for sustainable CO2 emission reduction and production of biofuel. These applications are highly dependent on microalgae biomass productivity of photobioreactor (PBR). The objective of this work is to optimize continuous flow PBR at steady state using a mathematical model describes growth of the microalgae species Chlorella vulgaris. The operating conditions that affect the performance of PBR are determined as pH, CO2 percentage in the gas feed, light intensity, and dilution rate. The MATLAB optimization function (fmincon) is used to find the best design and operating variables in the tested region. The maximum biomass productivity is achieved at the upper-bound of the range for pH, CO2 percentage in the gas feed, and light intensity, while for dilution rate, there exists an optimum value that guarantees maximum productivity. The maximum biomass productivity and specific growth rate were estimated as 4.03 and 0.196 billion cells/L h, respectively. This is achieved at optimum dilution rates of 0.049 and 1.0 h−1, respectively. The fmincon optimization results agree well with the literature that used different optimization methods. The model-based optimization predicts the best performance of PBR without conducting experiments. Sensitivity analysis of model constants on biomass concentration showed that mass transfer coefficient KLa has the highest sensitivity followed by µmax, KCL, and KE which has the lowest sensitivity for biomass production. The obtained results are of technological significance for processes such as CO2-fixation and biofuel production. Research effort is needed to exploit optimization results in large-scale cultivation.